Apparatus and method for reproducing optimized preference color using candidate images and natural languages

ABSTRACT

An apparatus and method are provided for reproducing an optimized preference color using candidate images and natural languages, in which user-oriented optimized picture quality can be provided through a printer. The apparatus includes a preference color-natural language information memory which stores characteristic information of a preference color mapped on a natural language, a candidate image provider module which provides candidate images having characteristic information applied to original images, and a candidate preference image input module which inputs one image, which satisfies a user&#39;s preference, among the candidate images.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based on and claims priority from Korean PatentApplication No. 10-2005-0120905, filed on Dec. 9, 2005 in the KoreanIntellectual Property Office, the disclosure of which is incorporatedherein in its entirety by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

Apparatuses and methods consistent with the present invention relate toreproducing an optimized preference color using candidate images andnatural languages and, more particularly, reproducing an optimizedpreference color using candidate images and natural languages, in whichcharacteristic information of a preference color mapped on a naturallanguage is applied to an original image to provide candidate images, apreference image among the candidate images is inputted, and colorinformation of the input preference image can be corrected.

2. Description of the Related Art

Digital imaging devices, which reproduce colors, such as monitors,scanners, and printers, have various functions and high quality tofulfill users' various demands. Also, the digital imaging devices usedifferent color spaces or different color models depending on theirrespective fields of use. Examples of the color models include a devicedependent color model and a device independent color model. The devicedependent color model includes an RGB color model corresponding to anadditive color space model, and a CMYK color model corresponding to asubtractive color space model. The device independent color modelincludes a CIE L*a*b* model, a CIE XYZ model, and a CIE LUV model. TheCMYK color model is used in the field of printing, while the RGB colormodel is used in the field of computer monitors, such as Internetgraphics.

When a user views images from a printer that outputs digital videoimages or a display device that displays images, a color, whichstimulates a user's visual perception and is preferred by the user in acolor gamut is referred to as a preference color. The preference coloraffects the performance of an output device such as a printer. To allowa user to obtain a preference color, related art techniques forreproducing and converting a preference color have been discussed.Examples of such related art techniques include a technique forautomatically converting a color gamut of flesh-color or sky-blue usinga previously defined matrix, and a technique for automaticallyconverting a skin color to a previously defined preference color.

However, such related art techniques have a problem in that they do notallow a user to execute image conversion by previously providing apreference image or to correct a converted image.

SUMMARY OF THE INVENTION

Exemplary embodiments of the present invention overcome the abovedisadvantages and other disadvantages not described above. Also, thepresent invention is not required to overcome the disadvantagesdescribed above, and an exemplary embodiment of the present inventionmay not overcome any of the problems described above.

The present invention provides an apparatus and method for reproducingan optimized preference color using candidate images and naturallanguages, in which characteristic information of a preference colormapped on a natural language is applied to an original image to providecandidate images, a preference image among the candidate images isinputted, and color information of the input preference image can becorrected.

The present invention also provides an apparatus and method forgenerating characteristic information of a preference color, whichgenerates characteristic information for reproducing a preference colorthat corresponds to the preference color, characteristics of thepreference color expressed by natural languages, and target coordinatescorresponding to the characteristics.

According to an aspect of the present invention, there is provided anapparatus for reproducing an optimized preference color using candidateimages and natural languages, which includes a preference color-naturallanguage information memory which stores characteristic information of apredetermined preference color mapped on a natural language, a candidateimage provider module which provides candidate images havingcharacteristic information applied to original images, and a candidatepreference image input module which inputs one image, which satisfies auser's preference, among the candidate images.

In another aspect of the present invention, there is provided anapparatus for generating characteristic information of a preferencecolor, which includes a preference color selection module which selectsone preference color of skin, sky-blue, and green grass, acharacteristic selection module which selects one of a plurality ofcharacteristics of the selected preference color expressed by naturallanguages, a target coordinate calculation module which calculatestarget coordinates corresponding to the selected characteristic, and acharacteristic information generation module which generatescharacteristic information for reproducing the preference color,corresponding to the preference color, the characteristic, and thetarget coordinates.

In still another aspect of the present invention, there is provided amethod of reproducing an optimized preference color using candidateimages and natural languages, which includes storing characteristicinformation of a predetermined preference color mapped on a naturallanguage, providing candidate images having characteristic informationapplied to original images, and inputting one image, which satisfies auser's preference, among the candidate images.

In further still another aspect of the present invention, there isprovided a method of generating characteristic information of apreference color, which includes selecting one preference color of skin,sky-blue, and green grass, selecting one of a plurality ofcharacteristics of the selected preference color expressed by naturallanguages, calculating target coordinates corresponding to the selectedcharacteristic, and generating characteristic information forreproducing the preference color, corresponding to the preference color,the characteristic, and the target coordinates.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other aspects of the present invention will become moreapparent from the following detailed description of exemplaryembodiments taken in conjunction with the accompanying drawings, inwhich:

FIG. 1 is a view illustrating the whole configuration of an apparatusfor reproducing an optimized preference color using candidate images andnatural languages in accordance with an exemplary embodiment of thepresent invention;

FIG. 2 is a view illustrating the construction of a candidate imageprovider module of FIG. 1;

FIG. 3 is a view illustrating a process of adjusting a preference colorto target coordinates using an image conversion function;

FIG. 4 is a view illustrating a graphic user interface that provides anoriginal image and a plurality of candidate images having characteristicinformation;

FIG. 5 is a view illustrating the construction of a color informationcorrection module of FIG. 1;

FIG. 6 is a view illustrating a graphic user interface that correctscolor information;

FIG. 7 is a view illustrating the construction of an apparatus forgenerating characteristic information for a preference color inaccordance with an exemplary embodiment of the present invention;

FIG. 8 is a table illustrating preference colors, characteristics ofpreference colors, and target coordinates;

FIG. 9 is a flowchart illustrating a method of reproducing an optimizedpreference color using candidate images and natural images in accordancewith an exemplary embodiment of the present invention; and

FIG. 10 is a flowchart illustrating a method of generatingcharacteristic information of a preference color in accordance with anexemplary embodiment of the present invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS OF THE INVENTION

Hereinafter, exemplary embodiments of the present invention will bedescribed in detail with reference to the accompanying drawings. Theaspects and features of the present invention and methods for achievingthe aspects and features will be apparent by referring to exemplaryembodiments to be described in detail with reference to the accompanyingdrawings. However, the present invention is not limited to the exemplaryembodiments disclosed hereinafter, but can be implemented in diverseforms. The matters defined in the description, such as the detailedconstruction and elements, are provided to assist those of ordinaryskill in the art in a comprehensive understanding of the invention, andthe present invention is only defined within the scope of the appendedclaims and their legal equivalents. In the entire description of thepresent invention, the same drawing reference numerals are used for thesame elements across various figures.

FIG. 1 is a view illustrating the whole configuration of an apparatusfor reproducing an optimized preference color using candidate images andnatural languages in accordance with an exemplary embodiment of thepresent invention. Referring to FIG. 1, the apparatus for reproducing anoptimized preference color using candidate images and natural languagesincludes a preference color-natural language information memory 100, acandidate image provider module 200, a candidate preference image inputmodule 300, and a color information correction module 400.

The preference color-natural language information memory 100 storescharacteristic information of a predetermined preference color mapped ona natural language, wherein the preference color effectively responds toa user's perception and includes a skin color, a sky-blue color, and agreen grass color. The preference color greatly affects the picturequality of a printed image. In FIG. 1, N_(skin) is a natural expressionof characteristics of a skin color, N_(sky) is a natural expression ofcharacteristics of a sky-blue color, and N_(grass) is a naturalexpression of characteristics of a green grass color. Meanwhile, fororiginal images expressed in FIG. 1, lightness showing brightness ofcolor is expressed as L_(i)*, chroma or saturation showing definition ofcolor is expressed as C_(i)*, and hue showing name of color is expressedas h_(i).

The candidate image provider module 200 is provided with characteristicinformation from the preference color-natural language informationmemory 100, wherein the characteristic information is mapped on naturallanguages N_(skin), N_(sky), and N_(grass). The candidate image providermodule 200 is also provided with the original images of L_(i)*, C_(i)*and h_(i). Thus, the candidate image provider module 200 serves toprovide candidate images obtained by applying the characteristicinformation to the original images. Since lightness L_(i)*, chromaC_(i)*, and hue hi of the original images are controlled throughprocessing steps by the candidate image provider module 200, L_(i)* isexpressed as L_(ip)*, C_(i)* is expressed as C_(ip)*, and h_(i) isexpressed as h_(ip). [291 If the user selects one candidate image, whichsatisfies its preference, among the candidate images provided from thecandidate image provider module 200, the candidate preference imageinput module 300 inputs the selected image. Finally, the colorinformation correction module 400 corrects the color information of theinput image to display an output image. In this case, it is noted thatlightness, chroma and hue of the output image are respectively expressedas L_(o)*, C_(o)* and h_(o).

The characteristic information used in FIG. 1 includes the preferencecolor, a plurality of characteristics of the preference color expressedby natural languages, and target coordinates corresponding to theplurality of characteristics. The characteristic information is used ina broader range than “characteristic.”

Hereinafter, the apparatus for reproducing an optimized preference colorusing candidate images and natural languages in accordance with anexemplary embodiment of the present invention will be described in moredetail with reference to FIGS. 2-6.

FIG. 2 is a view illustrating the construction of the candidate imageprovider module 200 of FIG. 1. The candidate image provider module 200includes an adjustment module 210 and a provider module 220.

As shown in FIG. 3, the adjustment module 210 adjusts the preferencecolors constituting the original images to colors corresponding to thetarget coordinates using a predetermined image conversion function. FIG.3 is a view illustrating a process of adjusting the preference colors tothe target coordinates by using the image conversion function.

FIG. 3 shows an L*a*b* color space of a CIE color model decided by theInternational Commission on Illumination (ICI), which decides thestandard of lighting apparatuses. The adjustment module 210 reflectsfive kinds of characteristics selected by the user in the skin color,the sky-blue color, and the green grass color to move the colors to thetarget coordinates {circle around (1)} to {circle around (5)}corresponding to the respective characteristics. In FIG. 3, the numbers{circle around (1)} to {circle around (5)} correspond to five kinds ofcharacteristics in a table as shown in FIG. 8.

The provider module 220 provides the plurality of candidate imagescomprised of the preference colors such as skin, sky-blue and grass,moved for adjustment to the target coordinates {circle around (1)} to{circle around (5)} corresponding to the respective characteristics. Theprovider module 220 can provide the plurality of candidate images usingsoft-proofing. Soft-proofing uses software to simulate a printed resultin a display device. This is shown in FIG. 4 which is a viewillustrating a graphic user interface that provides the plurality ofcandidate images and the original image having the characteristicinformation. Referring to FIG. 4, an upper image at the left is theoriginal image, and images corresponding to Preview 1 through Preview 5allow the user to preview the results adjusted to the target coordinatescorresponding to the five kinds of characteristics of the skin color,i.e., {circle around (1)} “clean”, {circle around (2)} “brilliant”,{circle around (3)}bright”, {circle around (4)} “mild”, and {circlearound (5)} “healthy.” A “Set Color” box of an upper right-hand side inFIG. 4 displays an interface for selecting one preference color amongthree kinds of preference colors, such as skin, sky-blue and greengrass. An “Execution” box of a lower right-hand side in FIG. 4 includesa “Preview” button, an “Apply to Image” button that allows a selectedcharacteristic to be applied to the original image, a “RGB2RGBLUT”button that allows conversion of RGB information, and a “Cancel” buttonthat allows cancellation of execution.

The user can select one image, which satisfies its preference, among theplurality of candidate images to which the respective characteristicsare applied by the interface, as illustrated in FIG. 4.

FIG. 5 is a view illustrating the construction of the color informationcorrection module 400 of FIG. 1. The color information correction module400 corrects color information of the input image to display an outputimage. The color information correction module 400 includes a preferencecolor input module 410 and a color component correction module 420.

The preference color input module 410 inputs a target preference colorto be corrected, among preference colors constituting the input image.The color component correction module 420 corrects a color component ofthe input preference color and displays an image of the corrected resultusing soft-proofing. Preferably, but not necessarily, the colorcomponent includes color information, such as lightness, chroma and hue,accustomed to general users.

The process of selecting the preference color to be corrected andcorrecting the color component of the selected preference color is shownin FIG. 6. FIG. 6 is a view illustrating a graphic user interface thatcorrects the color information. Referring to FIG. 6, an image of anupper left-hand side is the image (having the characteristicinformation) inputted by the candidate preference image input module300, and an image of a lower left-hand side is a preview image afterbeing corrected by the color information correction module 400. An upperright-hand side in FIG. 6 displays a “Preference Choices” box thatallows the user to select a region to be corrected, and a “Preferences”box that allows the preference color input module 410 to input thepreference color. It is noted from FIG. 6 that “skin” is marked tocorrect the skin color. A portion for correcting the color component isdisplayed in the “Reference Point” box below the “Preferences” box,wherein the user can input numerical values of lightness, saturation andhue to designate correction values. It is noted from FIG. 6 that thecolor component is corrected in the range of lightness of 58, saturationof 40, and hue of 59. Then, a “Color Control” interface allows the userto again adjust lightness, saturation and hue using an adjustmentslider. An “Execution” interface of the lower right-hand corner includesa “Candidates” button that allows the user to again select the candidateimage, an “LUT Gen.” button that allows a look-up table of lightness,saturation and hue to be displayed, a “To Image” button that displays acorrection image, and a “Cancel” button that allows cancellation ofexecution. Also, an “Original & Control Color” interface of the lowerleft-hand corner displays a color of the original image and a color ofthe corrected image to allow the user to identify the two colors at aglance.

Hereinafter, an apparatus for generating characteristic information,which is required to carry out the aforementioned apparatus of thepresent invention, will be described with reference to FIG. 7 and FIG.8.

FIG. 7 is a view illustrating the construction of an apparatus forgenerating characteristic information of a preference color inaccordance with an exemplary embodiment of the present invention, andFIG. 8 is a table illustrating preference colors, characteristics of thepreference colors, and target coordinates. Referring to FIG. 7, theapparatus 500 for generating characteristic information of thepreference color includes a preference color selection module 510, acharacteristic selection module 520, a target coordinate calculationmodule 530, and a characteristic information generation module 540.

The preference color selection module 510 selects one of preferencecolors, such as skin, sky-blue, and green glass, which constitute animage to be converted.

The characteristic selection module 520 allows the user to selectcharacteristics to be converted for the selected preference color. Inother words, the characteristic selection module 520 selects one of aplurality of characteristics expressed by natural languages for theselected preference color.

The target coordinate calculation module 530 calculates targetcoordinates corresponding to the selected characteristic.

The characteristic information generation module 540 generatescharacteristic information for reproducing a preference color,corresponding to the preference color, the characteristic and the targetcoordinates.

It is noted that characteristics of each preference color expressed bynatural languages and YCbCr values of target coordinates correspondingto the characteristics are exemplarily shown in FIG. 8. Referring toFIG. 8, characteristics of skin, sky-blue and green grass expressed byfive kinds of natural language interfaces are shown. The user can selectfive kinds of characteristics of the skin color, such as {circle around(1)} “clean”, {circle around (2)} “brilliant”, {circle around (3)}“bright”, {circle around (4)} “mild”, and {circle around (5)} “healthy,“and five kinds of characteristics of the sky-blue color, such as{circle around (1)} “bright”, {circle around (2)} “clear”, {circlearound (3)} “limpid”, {circle around (4)} “deep blue”, and {circlearound (5)} “purplish.” Likewise, the user can select five kinds ofcharacteristics of the green grass color, such as {circle around (1)}“bright”, {circle around (2)} “deep blue”, {circle around (3)} “light”,{circle around (4)} “vivid”, and {circle around (5)} “natural.” Colorperception of the table of FIG. 8 describes the concept of eachcharacteristic. For example, the characteristic {circle around (1)}“clean” of the skin color increases lightness and decreases saturation,the characteristic {circle around (1)} “bright” of the sky-blue colorincreases lightness, and the characteristic {circle around (1)} “bright”of the green grass color increases lightness and decreases shadow. It isnoted from the right of the table of FIG. 8 that YCbCr values of thetarget coordinates corresponding to the characteristics are calculatedand mapped.

In exemplary embodiments of the present invention, the term “unit”, thatis, “module” or “table”, as used herein, means, but is not limited to, asoftware or hardware component, such as a Field Programmable Gate Array(FPGA) or Application Specific Integrated Circuit (ASIC), which performscertain tasks. A module may advantageously be configured to reside onthe addressable storage medium and execute on one or more processors.Thus, a module may include, by way of example, components, such assoftware components, object-oriented software components, classcomponents and task components, processes, functions, attributes,procedures, subroutines, segments of program code, drivers, firmware,microcode, circuitry, data, databases, data structures, tables, arrays,and variables. The functionality provided for in the components andmodules may be combined into fewer components and modules or furtherseparated into additional components and modules. In addition, thecomponents and modules may be implemented so as to execute one or moreCPUs in a device.

A method of reproducing an optimized preference color will now bedescribed with reference to FIG. 9. In particular, FIG. 9 is a flowchartillustrating a method of reproducing an optimized preference color usingcandidate images and natural images in accordance with an exemplaryembodiment of the present invention.

First, the preference color-natural language information memory 100stores characteristic information of a predetermined preference colormapped on a natural language (S100). The preference color greatlyaffects the picture quality of a printed image and effectively respondsto the user's perception. Examples of the preference color include skin,sky-blue, and green grass. The characteristic information includes thepreference color, a plurality of characteristics of the preference colorexpressed by natural languages, and target coordinates corresponding tothe plurality of characteristics. The characteristic information is usedin a broader range than “characteristic.”

The candidate image provider module 200 provides candidate imagesobtained by applying the characteristics information to the originalimages (S200). In more detail, operation S200 includes adjusting thepreference colors constituting the original images to colorscorresponding to the target coordinates using an image conversionfunction and providing the plurality of candidate images of the adjustedpreference colors. The candidate image provider module 200 can providethe candidate images using soft-proofing.

The candidate preference image input module 300 inputs one image, whichsatisfies the user's preference, among the candidate images (S300).

Additionally, the color information correction module 400 can correctcolor information of the input image (S400). In more detail, theoperation 400 includes inputting the preference color to be correctedamong the preference colors constituting the input image, and correctingthe color component of the input preference color. The operation ofcorrecting the color component of the input preference color can includedisplaying the image of the corrected result of the color componentusing soft-proofing. Preferably, but not necessarily, the colorcomponent includes color information, such as lightness, chroma and hue,accustomed to general users.

FIG. 10 is a flowchart illustrating a method of generating thecharacteristic information of the preference color in accordance with anexemplary embodiment of the present invention.

Referring to FIG. 10, the preference color selection module 510 selectsone of the preference colors such as skin, sky-blue and green grass(S510). The characteristic selection module 520 selects one of aplurality of characteristics of the selected preference color expressedby natural languages (S500). The target coordinate calculation module530 calculates the target coordinates corresponding to the selectedcharacteristic (S530). Finally, the characteristic informationgeneration module 540 generates characteristic information forreproducing the preference color, corresponding to the preference color,the characteristic and the target coordinates (S540).

Meanwhile, it is apparent to those skilled in the art that the scope ofthe apparatus for reproducing an optimized preference color usingcandidate images and natural languages according to exemplaryembodiments of the present invention is extended to a computerprogrammable recording medium that can record the aforementioned methodusing a computer.

As described above, the apparatus and method for reproducing anoptimized preference color using candidate images and natural languagesaccording to the exemplary embodiments of the present invention have thefollowing advantages.

The characteristic information of the preference color mapped on thenatural language is applied to the original images to provide thecandidate images, and a preference of one of the candidate images isinputted, and color information of the input image can be corrected.

Also, in the apparatus and method for generating characteristicinformation of a preference color, the preference color, characteristicsof the preference color expressed by the natural languages, and thetarget coordinates corresponding to the characteristics correspond tocharacteristic information for reproducing the preference color.

Accordingly, it is possible to provide user-oriented optimized picturequality through a printer to which exemplary embodiments of the presentinvention are applied.

The exemplary embodiments of the present invention have been describedfor illustrative purposes, and those skilled in the art will appreciatethat various modifications, additions and substitutions are possiblewithout departing from the scope and spirit of the invention asdisclosed in the accompanying claims. Therefore, the scope of thepresent invention should be defined by the appended claims and theirlegal equivalents.

1. An apparatus for reproducing an optimized preference color usingcandidate images and natural languages, the apparatus comprising: apreference color-natural language information memory which storescharacteristic information of a preference color mapped on a naturallanguage; a candidate image provider module which provides candidateimages having characteristic information applied to original images; anda candidate preference image input module which inputs one image, whichsatisfies a user's preference, among the candidate images.
 2. Theapparatus of claim 1, further comprising a color information correctionmodule which corrects color information of the input image.
 3. Theapparatus of claim 1, wherein the preference color is one of skin, blueand green.
 4. The apparatus of claim 1, wherein the characteristicinformation includes the preference color, a plurality ofcharacteristics of the preference color expressed by natural languages,and target coordinates corresponding to the plurality ofcharacteristics.
 5. The apparatus of claim 4, wherein the candidateimage provider module comprises: an adjustment module which adjustspreference colors constituting original images to colors correspondingto the target coordinates using an image conversion function; and aprovider module which provides a plurality of candidate images comprisedof the adjusted preference colors.
 6. The apparatus of claim 5, whereinthe provider module provides the plurality of candidate images usingsoft-proofing.
 7. The apparatus of claim 2, wherein the colorinformation correction module comprises: a preference color input modulewhich inputs a preference color to be corrected among preference colorsconstituting the input image; and a color component correction modulewhich corrects a color component of the input preference color.
 8. Theapparatus of claim 7, wherein the color component correction moduledisplays an image of the corrected result of the color component usingsoft-proofing.
 9. The apparatus of claim 7, wherein the color componentis one of lightness, chroma, and hue.
 10. An apparatus for generatingcharacteristic information of a preference color, the apparatuscomprising: a preference color selection module which selects onepreference color of skin, blue, and green; a characteristic selectionmodule which selects one of a plurality of characteristics of theselected preference color expressed by natural languages; a targetcoordinate calculation module which calculates target coordinatescorresponding to the selected characteristic; and a characteristicinformation generation module which generates characteristic informationfor reproducing the preference color, wherein the characteristicinformation comprises the preference color, the characteristic, and thetarget coordinates.
 11. A method of reproducing an optimized preferencecolor using candidate images and natural languages, the methodcomprising: storing characteristic information of a preference colormapped on a natural language; providing candidate images havingcharacteristic information applied to original images; and inputting oneimage, which satisfies a user's preference, among the candidate images.12. The method of claim 11, further comprising correcting colorinformation of the input image.
 13. The method of claim 11, wherein thepreference color is one of skin, blue and green.
 14. The apparatus ofclaim 11, wherein the characteristic information includes the preferencecolor, a plurality of characteristics of the preference color expressedby natural languages, and target coordinates corresponding to theplurality of characteristics.
 15. The method of claim 14, whereinproviding the candidate images comprises: adjusting preference colorsconstituting original images to colors corresponding to the targetcoordinates using an image conversion function; and providing theplurality of candidate images, which comprise the adjusted preferencecolors.
 16. The method of claim 15, wherein providing the plurality ofcandidate images further comprises using soft-proofing.
 17. The methodof claim 12, wherein correcting the color information comprises:inputting a preference color to be corrected among preference colorsconstituting the input image; and correcting a color component of theinput preference color.
 18. The method of claim 17, wherein correctingthe color component comprises displaying an image of the correctedresult of the color component using soft-proofing.
 19. The method ofclaim 17, wherein the color component is one of lightness, chroma, andhue.
 20. A method of generating characteristic information of apreference color, the method comprising: selecting one preference colorof skin, blue, and green; selecting one of a plurality ofcharacteristics of the selected preference color expressed by naturallanguages; calculating target coordinates corresponding to the selectedcharacteristic; and generating characteristic information forreproducing the preference color, which comprises the preference color,the characteristic, and the target coordinates.
 21. A computer-readablerecording medium recorded with a program code for a computer to executea method of reproducing an optimized preference color using candidateimages and natural languages, the method comprising: storingcharacteristic information of a preference color mapped on a naturallanguage; providing candidate images having characteristic informationapplied to original images; and inputting one image, which satisfies auser's preference, among the candidate images.
 22. A computer-readablerecording medium recorded with a program code for a computer to executea method of generating characteristic information of a preference color,the method comprising: selecting one preference color of skin, blue, andgreen; selecting one of a plurality of characteristics of the selectedpreference color expressed by natural languages; calculating targetcoordinates corresponding to the selected characteristic; and generatingcharacteristic information for reproducing the preference color, whichcomprises the preference color, the characteristic, and the targetcoordinates